Hand gesture recognition algorithm based on grayscale histogram of the image

Igorevich, Rustam Rakhimov; Park, Pusik; Dai, Min; Park, Yunjung; Choi, Jeong-Yeol; Choi, Eunmi

doi:10.1109/icaict.2010.5612056

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…et al [11] implemented a tracking algorithm based on gray scale histogram values of images for detecting hand motion by simple stereo camera. The hand was tracked and recognized which could choose distance from camera.…”

Section: Earlier Workmentioning

confidence: 99%

Design and development of tamil sign alphabets using image processing with right hand palm to aid deaf-dumb people

Rajam¹,

Balakrishnan²

2013

IETE J Res

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Hand recognition is a recent active area of research in the computer vision for the purpose of Human -Computer Interaction. This paper mainly concentrates on Tamil sign alphabets (TSL) into speech which could be helpful for deaf-dumb people. In this paper, a set of 32 (2 5 ) combinations of binary number sign images are introduced to propose a system to recognize Tamil sign alphabets. These Tamil alphabets have 12 vowels, 18 consonants, and one Aayutha Ezhuthu. The proposed system is based on four main stages: Pre-processing method, Training phase, Sign detection, and Conversion of Binary to voice. The binary sign images are loaded at a run time or static as 310 images which are taken ten times in different distances at the same position. The five fingertip positions represent ('1' or '0') and are identified by using image processing techniques with proposed right hand palm angular-based analysis. Then, the binary values are assigned to the corresponding Tamil letters and voice. The experiments were performed with ten different signer palms and the results demonstrated that the system could successfully recognize Tamil sign alphabets with better accuracy with 99.35% of static images and 98.36% of dynamic images (runtime).

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Section: Earlier Workmentioning

confidence: 99%

Design and development of tamil sign alphabets using image processing with right hand palm to aid deaf-dumb people

Rajam¹,

Balakrishnan²

2013

IETE J Res

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show abstract

“…For that we are referring to [5], where we are calculating threshold value for the filtering by depth grayscale value. Usually in gesture recognition systems based on stereo camera, threshold of the depth map filtering has a fixed value.…”

Section: Introductionmentioning

confidence: 99%

“…The threshold of abstract zone can be fixed or it can be defined as a dynamic. In [5] shown how to define dynamic threshold based on grayscale histogram values of the depth map frame. Dynamic depth map threshold value makes system more flexible and motions performed by hand could be detected from different distances.…”

Section: Gesture Recognition Algorithmmentioning

confidence: 99%

“…To avoid this case third step of the algorithm should be changed. Algorithm to find threshold value for two different outstretched hands, using grayscale histogram: 1) Detect first hand by [5] 2) Perform skin color detection over first detected hand 3) Continuously scan grayscale histogram, until next extreme point was found 4) Skin-color scanning in received blob 5) Checking blob region to not being face This algorithm will define two threshold values for two different outstretched hands, using these threshold values possible to track both hands from any location. As shown in Fig.4.…”

Section: Two Hand Recognition and Trackingmentioning

confidence: 99%

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Two Hand Gesture Recognition Using Stereo Camera

Igorevich¹,

Park²,

Choi³

et al. 2013

IJCEE

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Abstract-This paper proposes method for gesture recognition by two hands. In this research stereo camera was used to calculate depth map of the frame. Based on depth information precise tracking of the hands was applied. Depth map calculates in hardware level. Oversensitivity of camera to light generates horizontal noise. Especially appeared horizontal noise affects on tracking two hands located in same altitude. In this paper we suggest masking method to avoid horizontal noise in software level.Index Terms-Hand tracking, stereo camera, two hand gesture recognition, horizontal noise, dynamic programming, depth map.

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“…The main reason of these technologies becomes more popular is because it can be applied into many different fields easily and efficiently. Especially, gesture recognition easily can be applied to the web services, smart home systems, robot manipulation and games [2]. That is why tracking non-rigid motions from sequential videos have been a great interest to the computer vision community.…”

Section: Introductionmentioning

confidence: 99%